bims-tumhet Biomed News
on Tumor heterogeneity
Issue of 2025–05–18
eleven papers selected by
Sergio Marchini, Humanitas Research
  1. Genomic Profiling in Patients with Endometrial Cancer by Deep Sequencing of Vaginal Swabs and Plasma.
  2. Cell-type deconvolution methods for spatial transcriptomics.
  3. Targeting vulnerabilities of aneuploid cells for cancer therapy.
  4. Spatial Omics in Clinical Research: A Comprehensive Review of Technologies and Guidelines for Applications.
  5. Unravelling the tumor microenvironment and PD-L1 expression across tissue type in high-grade serous ovarian cancer in the NeoPembrOV/GINECO phase II randomized trial.
  6. The new 2023 endometrial cancer FIGO staging system: balancing innovation with complexity.
  7. The past, present, and future of FIGO staging of endometrial cancer.
  8. The application of cell-free DNA methylation patterns in critical illnesses: A protocol paper.
  9. Role of tumor microenvironment in ovarian cancer metastasis and clinical advancements.
  10. The predictive power of profiling the DNA methylome in human health and disease.
  11. Combining spatial transcriptomics with tissue morphology.
  1. Clin Cancer Res. 2025 May 13.
    Genomic Profiling in Patients with Endometrial Cancer by Deep Sequencing of Vaginal Swabs and Plasma.
    Namsoo Kim, Yoo-Na Kim, Kyunglim Lee, Eunhyang Park, Yong Jae Lee, Eunha Baek, Seungki Min, Jihyang Park, Zisun Choi, Saeam Shin, Sang Wun Kim, Sunghoon Kim, Jong Rak Choi, Seung-Tae Lee, Jung-Yun Lee.
       INTRODUCTION: Endometrial cancer is a common gynecologic malignancy lacks effective non-invasive screening tools, as traditional approaches rely on invasive biopsies. In this large prospective study, we evaluated a novel approach combining vaginal swab DNA and plasma-based circulating tumor DNA (ctDNA) for genomic profiling to provide a comprehensive framework for diagnosis, prognosis, and disease monitoring.
    MATERIALS AND METHODS: Adult patients with diverse stages of endometrial cancer, pre-neoplastic disease, and benign endometrial conditions were prospectively recruited over two years. Paired vaginal swab DNA and plasma-based ctDNA were collected pre-operatively, and additional plasma samples were obtained multiple time points post-operatively. Deep next-generation sequencing targeting 101 genes was performed, achieving an average depth exceeding 40,000x.
    RESULTS: A total of 191 patients contributed 388 samples. Vaginal swab DNA demonstrated 77.7% sensitivity and 96.6% specificity. PTEN mutations were associated with favorable prognosis (hazard ratio: 0.27; 95% CI: 0.092-0.77) and TP53 mutations were associated with poor prognosis (hazard ratio: 3.7; 95% CI: 1.4-10). A novel classification system based on the mutational profile of PTEN/TP53 identified distinct prognostic groups. Plasma-based ctDNA was significantly associated with stage, lymphovascular invasion, and prognosis (p < 0.01 for all). Patients with pre-operative positive plasma-based ctDNA results exhibited poorer outcomes (p < 0.01), whereas post-operative positive ctDNA enabled early detection of recurrence.
    DISCUSSION: These two non-invasive methods have distinct, complementary roles in the management of endometrial cancer. Vaginal swab DNA and novel PTEN/TP53-based classification have distinct prognostic advantages over existing frameworks. Plasma-based ctDNA provides dynamic insights into recurrence risk and disease progression.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-24-4263
  2. Nat Rev Genet. 2025 May 14.
    Cell-type deconvolution methods for spatial transcriptomics.
    Lucie C Gaspard-Boulinc, Luca Gortana, Thomas Walter, Emmanuel Barillot, Florence M G Cavalli.
      Spatial transcriptomics is a powerful method for studying the spatial organization of cells, which is a critical feature in the development, function and evolution of multicellular life. However, sequencing-based spatial transcriptomics has not yet achieved cellular-level resolution, so advanced deconvolution methods are needed to infer cell-type contributions at each location in the data. Recent progress has led to diverse tools for cell-type deconvolution that are helping to describe tissue architectures in health and disease. In this Review, we describe the varied types of cell-type deconvolution methods for spatial transcriptomics, contrast their capabilities and summarize them in a web-based, interactive table to enable more efficient method selection.
    DOI:  https://doi.org/10.1038/s41576-025-00845-y
  3. Trends Cancer. 2025 May 13. pii: S2405-8033(25)00097-4. [Epub ahead of print]
    Targeting vulnerabilities of aneuploid cells for cancer therapy.
    Johanna Zerbib, Amit Bloomberg, Uri Ben-David.
      Aneuploidy is a common feature of cancer that drives tumor evolution, but it also creates cellular vulnerabilities that might be exploited therapeutically. Recent advances in genomic technologies and experimental models have uncovered diverse cellular consequences of aneuploidy, revealing dependencies on mitotic regulation, DNA replication and repair, proteostasis, metabolism, and immune interactions. Harnessing aneuploidy for precision oncology requires the combination of genomic, functional, and clinical studies that will enable translation of our improved understanding of aneuploidy to targeted therapies. In this review we discuss approaches to targeting both highly aneuploid cells and cells with specific common aneuploidies, summarize the biological underpinning of these aneuploidy-induced vulnerabilities, and explore their therapeutic implications.
    Keywords:  aneuploidy; cancer therapy; genome instability; precision medicine
    DOI:  https://doi.org/10.1016/j.trecan.2025.04.005
  4. Int J Mol Sci. 2025 Apr 22. pii: 3949. [Epub ahead of print]26(9):
    Spatial Omics in Clinical Research: A Comprehensive Review of Technologies and Guidelines for Applications.
    Yoonji Lee, Mingyu Lee, Yoojin Shin, Kyuri Kim, Taejung Kim.
      Spatial omics integrates molecular profiling with spatial tissue context, enabling high-resolution analysis of gene expression, protein interactions, and epigenetic modifications. This approach provides critical insights into disease mechanisms and therapeutic responses, with applications in cancer, neurology, and immunology. Spatial omics technologies, including spatial transcriptomics, proteomics, and epigenomics, facilitate the study of cellular heterogeneity, tissue organization, and cell-cell interactions within their native environments. Despite challenges in data complexity and integration, advancements in multi-omics pipelines and computational tools are enhancing data accuracy and biological interpretation. This review provides a comprehensive overview of key spatial omics technologies, their analytical methods, validation strategies, and clinical applications. By integrating spatially resolved molecular data with traditional omics, spatial omics is transforming precision medicine, biomarker discovery, and personalized therapy. Future research should focus on improving standardization, reproducibility, and multimodal data integration to fully realize the potential of spatial omics in clinical and translational research.
    Keywords:  spatial epigenomics; spatial omics; spatial omics data analysis tools; spatial proteomics; spatial transcriptomics
    DOI:  https://doi.org/10.3390/ijms26093949
  5. Clin Cancer Res. 2025 May 16.
    Unravelling the tumor microenvironment and PD-L1 expression across tissue type in high-grade serous ovarian cancer in the NeoPembrOV/GINECO phase II randomized trial.
    Laetitia Collet, Maude Ardin, David Venet, Justine Berthet, Sarah Ghamry-Barrin, Isabelle Treilleux, Jean-Christophe Noel, Marianne Leheurteur, Jérôme Meunier, Leïla Bengrine Lefevre, Mathilde Martinez, Frank Priou, Frédéric Selle, Pierre-Alexandre Just, Guillaume Bataillon, Françoise Rothé, Christos Sotiriou, Christophe Caux, Bertrand Dubois, Isabelle Ray-Coquard, Olivia Le Saux.
       PURPOSE: To describe PD-L1 expression across tissue types and its associated tumor microenvironment (TME) and to investigate how it impacts its predictive value for response to pembrolizumab in treatment-naïve ovarian cancer (OC) patients included in the NeoPembrOV phase II trial (NCT03275506).
    METHODS: PD-L1 expression was assessed for 85 patients (56 on metastasis, 29 on tubo-ovary) using tumor proportion score (TPS) and immune cell (IC) score, considering positivity if ≥ 1% and high expression if ≥ 5%. RNA sequencing and multiplex immunofluorescence were conducted. The Australian Ovarian Cancer Study (AOCS) was used as an external validation cohort.
    RESULTS: PD-L1 was primarily expressed by tumor cells (TCs) in tubo-ovaries and by ICs in metastases. IC-score assessed on the metastases was associated with a longer PFS in the pembrolizumab arm compared to the control arm. Compared to tubo-ovaries, metastases were enriched in T and B cells as well as in GZMBCD8 cytotoxic T cell signatures. In metastases, IC-score was associated with immune infiltration and overexpression of additional immune checkpoints such as IDO1, LAG3, ICOS while TPS was associated with cell proliferation, immune infiltration and interferon-gamma pathways. In tubo-ovaries, TPS was associated with pathways linked to cell proliferation and antigen presentation but depleted in activated immune pathways, and CD274 expression was correlated with hypoxia and PI3K/Akt/mTOR signaling.
    DISCUSSION: Distinct PD-L1 expression patterns across tissue type are associated with different biological pathways and TME in OC impacting PD-L1 predictive value. Our results provide novel insights in HGSC biology for tailoring immunotherapy in OC patients.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-24-2712
  6. Int J Gynecol Cancer. 2025 Apr 11. pii: S1048-891X(25)00942-9. [Epub ahead of print] 101823
    The new 2023 endometrial cancer FIGO staging system: balancing innovation with complexity.
    Emilia Palmieri, Andrea Mariani, Robert Coleman, Sabrina Croce, Pei Hui, Sigurd Lax, Xavier Matias-Guiu, David Mutch, Giovanni Scambia, Jalid Sehouli, Brian M Slomovitz, Simona Stolnicu, Christina Fotopoulou, Nicole Concin.
      In August 2023, the International Federation of Gynecology and Obstetrics introduced an updated staging system for endometrial cancer that integrates histopathologic and molecular characteristics (optional) of the tumor alongside with anatomic extent of the disease. This innovative approach aims to improve the prognostication of the system and the identification of treatment-relevant patient populations by more accurately stratifying patients based on tumor biology, representing a significant advancement toward personalized medicine. However, its implementation poses challenges, including the heterogeneous availability of molecular testing worldwide, and the need for further standardization and prospective validation of some of the newly introduced histopathological parameters. To address these innovations and related controversies, a meeting of physicians, including gynecologic oncologists and pathologists, was held. This article summarizes the reflections that emerged from this meeting, focusing on key elements such as the integration of histopathologic features (eg, "high-grade, aggressive histologic types," "substantial lymphovascular space invasion"), molecular classification, and the implications for global reproducibility and applicability. It also addresses the basic approach toward staging: should it offer integrated, patient-relevant information to enable accurate prognostication and inform treatment decisions or should a staging system simply provide a common language to communicate disease extent? The meeting provided an opportunity for a group of physicians to share considerations on this evolving topic. Our article highlights focal points of change in the new staging system and identifies key areas for future research, advocating for collaborative efforts to generate more robust evidence on some variables introduced in the staging system through prospective studies. By addressing these challenges, we aim to improve the applicability and effectiveness of the new International Federation of Gynecology and Obstetrics staging system in real-world scenarios and identify elements that may require further refinement, ultimately advancing precision medicine in endometrial cancer care.
    Keywords:  Endometrial Neoplasms; Gynecologic Neoplasms; Uterine Neoplasms
    DOI:  https://doi.org/10.1016/j.ijgc.2025.101823
  7. J Gynecol Oncol. 2025 Apr 14.
    The past, present, and future of FIGO staging of endometrial cancer.
    Xiaoyan Zhao, Fujing Sun, Nankun Leng, Xin Zhang, Yanmei Zhu.
      The International Federation of Gynecology and Obstetrics (FIGO) staging of endometrial cancer (EC) is regarded as a crucial tool for guiding treatment, evaluating prognosis, and advancing clinical research. It is a concept of shared importance among gynecologic oncologists, pathologists, and patients with EC. In June 2023, the International Federation of Gynecology and Obstetrics released a new staging system for EC. This review aims to discuss comprehensively the developmental trajectory of FIGO staging for EC, focusing on the differences between the 2023 FIGO and earlier staging systems, and delineating the advantages and disadvantages of incorporating various pathological factors and molecular subtypes into staging. The article emphasizes the progress made with the updated 2023 FIGO version in improving prognostic prediction accuracy for patients with EC. However, as the staging categories expand, their complexity becomes increasingly apparent, potentially impacting health care professionals' accurate understanding and application of staging. Moreover, unresolved issues persist regarding histological types and grading, lymphovascular space invasion, and molecular subtypes, as well as distinguishing between low-grade endometrioid carcinomas confined to the uterus and ovaries, which may affect the personalized management of patients with EC. In the future, these issues still require extensive clinical research and specific data for validation or confirmation, presenting a challenge shared by gynecologic oncologists and pathologists.
    Keywords:  Endometrial Cancer; FIGO; Molecular Typing; Neoplasm Staging
    DOI:  https://doi.org/10.3802/jgo.2025.36.e105
  8. PLoS One. 2025 ;20(5): e0321626
    The application of cell-free DNA methylation patterns in critical illnesses: A protocol paper.
    Shih-Han Kao, K Greer Stumpf, Hunter A Gaudio, John C Greenwood, Samuel S Shin, Frances S Shofer, David H Jang.
      Biomarkers in clinical medicine are typically employed to gauge severity of disease, prognosis and to monitor response to treatment. While various biomarkers have been employed in clinical medicine with variable performance characteristics, the use of cell-free DNA (cfDNA) have gained increased traction as a novel biomarker in a wide range of disease states such as cancer and trauma. While the quantification of cfDNA have been correlated with disease severity, the use of methylation pattens of cfDNA can be used to localize the site of injury that may have implications regarding prognosis and therapeutics. We propose a procedure using samples in a swine model of cardiac arrest where carbon monoxide is being used as a therapeutic to demonstrate our method and feasibility to obtain plasma cfDNA methylation patterns to help identify tissue origin with potential application in critical care medicine.
    DOI:  https://doi.org/10.1371/journal.pone.0321626
  9. J Transl Med. 2025 May 14. 23(1): 539
    Role of tumor microenvironment in ovarian cancer metastasis and clinical advancements.
    Yang Wang, Na Zhu, Jing Liu, Fang Chen, Yang Song, Yue Ma, Zhuo Yang, Danbo Wang.
      Ovarian cancer (OC) is the most lethal gynecological malignancy worldwide, characterized by heterogeneity at the molecular, cellular and anatomical levels. Most patients are diagnosed at an advanced stage, characterized by widespread peritoneal metastasis. Despite optimal cytoreductive surgery and platinum-based chemotherapy, peritoneal spread and recurrence of OC are common, resulting in poor prognoses. The overall survival of patients with OC has not substantially improved over the past few decades, highlighting the urgent necessity of new treatment options. Unlike the classical lymphatic and hematogenous metastasis observed in other malignancies, OC primarily metastasizes through widespread peritoneal seeding. Tumor cells (the "seeds") exhibit specific affinities for certain organ microenvironments (the "soil"), and metastatic foci can only form when there is compatibility between the "seeds" and "soil." Recent studies have highlighted the tumor microenvironment (TME) as a critical factor influencing the interactions between the "seeds" and "soil," with ascites and the local peritoneal microenvironment playing pivotal roles in the initiation and progression of OC. Prior to metastasis, the interplay among tumor cells, immunosuppressive cells, and stromal cells leads to the formation of an immunosuppressive pre-metastatic niche in specific sites. This includes characteristic alterations in tumor cells, recruitment and functional anomalies of immune cells, and dysregulation of stromal cell distribution and function. TME-mediated crosstalk between cancer and stromal cells drives tumor progression, therapy resistance, and metastasis. In this review, we summarize the current knowledge on the onset and metastatic progression of OC. We provide a comprehensive discussion of the characteristics and functions of TME related to OC metastasis, as well as its association with peritoneal spread. We also outline ongoing relevant clinical trials, aiming to offer new insights for identifying potential effective biomarkers and therapeutic targets in future clinical practice.
    Keywords:  Growth; Immune cells; Metastasis; Ovarian cancer; Stromal cells; Tumor microenvironment
    DOI:  https://doi.org/10.1186/s12967-025-06508-0
  10. Epigenomics. 2025 May 10. 1-12
    The predictive power of profiling the DNA methylome in human health and disease.
    Paraskevi Christofidou, Christopher G Bell.
      Early and accurate diagnosis significantly improves the chances of disease survival. DNA methylation (5mC), the major DNA modification in the human genome, is now recognized as a biomarker of immense clinical potential. This is due to its ability to delineate precisely cell-type, quantitate both internal and external exposures, as well as tracking chronological and biological components of the aging process. Here, we survey the current state of DNA methylation as a biomarker and predictor of traits and disease. This includes Epigenome-wide association study (EWAS) findings that inform Methylation Risk Scores (MRS), EpiScore long-term estimators of plasma protein levels, and machine learning (ML) derived DNA methylation clocks. These all highlight the significant benefits of accessible peripheral blood DNA methylation as a surrogate measure. However, detailed DNA methylation biopsy analysis in real-time is also empowering pathological diagnosis. Furthermore, moving forward, in this multi-omic and biobank scale era, novel insights will be enabled by the amplified power of increasing sample sizes and data integration.
    Keywords:  DNA methylation; EWAS; Epigenetics; biological ageing; epigenetic clocks; epigenetic estimators; epigenomics; methylation risk scores
    DOI:  https://doi.org/10.1080/17501911.2025.2500907
  11. Nat Commun. 2025 May 13. 16(1): 4452
    Combining spatial transcriptomics with tissue morphology.
    Eduard Chelebian, Christophe Avenel, Carolina Wählby.
      Spatial transcriptomics has transformed our understanding of tissue architecture by preserving the spatial context of gene expression patterns. Simultaneously, advances in imaging AI have enabled extraction of morphological features describing the tissue. This review introduces a framework for categorizing methods that combine spatial transcriptomics with tissue morphology, focusing on either translating or integrating morphological features into spatial transcriptomics. Translation involves using morphology to predict gene expression, creating super-resolution maps or inferring genetic information from H&E-stained samples. Integration enriches spatial transcriptomics by identifying morphological features that complement gene expression. We also explore learning strategies and future directions for this emerging field.
    DOI:  https://doi.org/10.1038/s41467-025-58989-8
This page is being maintained by Thomas Krichel. It was last updated on 2025‒05‒27 at 14:48.